{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3f43eec2-2a4c-48a0-9786-c02bebafea2d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Obtaining file:///dss/dsshome1/04/di93zer/git/cellnet\n",
      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
      "\u001b[?25hInstalling collected packages: cellnet\n",
      "  Running setup.py develop for cellnet\n",
      "Successfully installed cellnet\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.1.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython3 -m pip install --upgrade pip\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "!pip install -e /dss/dsshome1/04/di93zer/git/cellnet --no-deps"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6700509-52e1-4506-930c-60899501b154",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Visualize training dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0016e431-024b-4f40-9cbd-f80363e976e1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "from os.path import join\n",
    "\n",
    "import tensorboard as tb\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b2ceda58-dc8f-4ea9-9ecd-17e96446c4e9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# logs under: https://tensorboard.dev/experiment/oYB2aPfzTQmXj07sJ7KOFg/\n",
    "experiment_id = 'oYB2aPfzTQmXj07sJ7KOFg'\n",
    "experiment = tb.data.experimental.ExperimentFromDev(experiment_id)\n",
    "df = experiment.get_scalars()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "26e245be-f190-48ac-9354-3e073dae03dc",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "LOGS_PATH = '/mnt/dssfs02/tb_logs/cxg_2023_05_15_tabnet/default'\n",
    "\n",
    "AUGMENTED = [f'augmentation=True_subset=30_run{i}' for i in range(1, 5)]\n",
    "NON_AUGMENTED = [f'augmentation=False_subset=30_run{i}' for i in range(1, 5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "89a24e77-f40f-40e9-98ec-c01f8d6f1b81",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_data(data, versions, columns):\n",
    "    dfs = []\n",
    "    for version in versions:\n",
    "        if isinstance(version, str):\n",
    "            version = [version]\n",
    "        dfs.append(\n",
    "            data[data.run.isin(version)]\n",
    "            .drop_duplicates(subset=['step', 'tag'], keep='last')\n",
    "            .pivot(index='step', columns='tag', values='value')\n",
    "            [columns]\n",
    "            .dropna()\n",
    "            .assign(version=version[0])\n",
    "        )\n",
    "        \n",
    "    return pd.concat(dfs)\n",
    "\n",
    "\n",
    "val_cols = ['epoch', 'val_loss', 'val_f1_macro', 'val_f1_micro']\n",
    "df_val_augmented = get_data(df, AUGMENTED, val_cols).assign(data_augmentation=True)\n",
    "df_val_non_augmented = get_data(df, NON_AUGMENTED, val_cols).assign(data_augmentation=False)\n",
    "\n",
    "train_cols = ['epoch', 'train_loss', 'train_f1_macro_step']\n",
    "df_train_augmented = get_data(df, AUGMENTED, train_cols).assign(data_augmentation=True).reset_index()\n",
    "df_train_non_augmented = get_data(df, NON_AUGMENTED, train_cols).assign(data_augmentation=False).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ab6f5779-5662-44c8-a296-ae1fb9dccda7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_best_ckpts(logs_path, versions):\n",
    "    epochs = []\n",
    "    best_ckpts = []\n",
    "    \n",
    "    for version in versions:\n",
    "        # sort first -> in case both f1-score are the same -> take the one which was trained for less epochs\n",
    "        files = sorted([file for file in os.listdir(join(logs_path, version, 'checkpoints')) if 'val_f1_macro' in file])\n",
    "        f1_scores = [float(re.search('val_f1_macro=(.*?).ckpt', file).group(1)) for file in files]\n",
    "        best_ckpt = files[np.argmax(f1_scores)]\n",
    "        epochs.append(int(re.search('epoch=(.*?)_val_f1_macro', best_ckpt).group(1)))\n",
    "        best_ckpts.append(join(logs_path, version, 'checkpoints', best_ckpt))\n",
    "\n",
    "    return best_ckpts, np.mean(epochs)\n",
    "\n",
    "\n",
    "best_ckpts_augmented, avg_train_time_augmented = get_best_ckpts(LOGS_PATH, AUGMENTED)\n",
    "best_ckpts_non_augmented, avg_train_time_non_augmented = get_best_ckpts(LOGS_PATH, NON_AUGMENTED)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46efd144-4db0-4661-a254-5c6bdbbcac54",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2a40ba59-7b15-4d57-aecd-bcc8b5796211",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Validation metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7aec1835-04f0-4157-8014-902d0cfa5e27",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1150x460 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 2, sharex=True, figsize=(11.5, 4.6))\n",
    "\n",
    "sns.lineplot(x='epoch', y='val_loss', hue='data_augmentation', data=pd.concat([df_val_augmented, df_val_non_augmented]), ax=axs[0, 0])\n",
    "axs[0, 0].set_ylabel('Loss (Cross Entropy)')\n",
    "axs[0, 0].set_ylim(0.475, 0.7)\n",
    "axs[0, 0].axvline(avg_train_time_augmented, color='#ff7f0e', ls=':')\n",
    "axs[0, 0].axvline(avg_train_time_non_augmented, color='#1f77b4', ls=':')\n",
    "axs[0, 0].get_legend().remove()\n",
    "\n",
    "sns.lineplot(x='epoch', y='val_f1_macro', hue='data_augmentation', data=pd.concat([df_val_augmented, df_val_non_augmented]), ax=axs[1, 0])\n",
    "axs[1, 0].set_ylabel('F1-score (macro avg.)')\n",
    "axs[1, 0].axvline(avg_train_time_augmented, color='#ff7f0e', ls=':')\n",
    "axs[1, 0].axvline(avg_train_time_non_augmented, color='#1f77b4', ls=':')\n",
    "axs[1, 0].get_legend().remove()\n",
    "\n",
    "\n",
    "sns.lineplot(\n",
    "    x='epoch', y='train_loss', hue='data_augmentation', \n",
    "    data=pd.concat([df_train_augmented, df_train_non_augmented]),\n",
    "    ax=axs[0, 1]\n",
    ")\n",
    "axs[0, 1].set_ylabel('')\n",
    "axs[0, 1].set_yscale('log')\n",
    "axs[0, 1].set_ylim(5e-3, 1.)\n",
    "axs[0, 1].get_legend().remove()\n",
    "\n",
    "sns.lineplot(\n",
    "    x='epoch', y='train_f1_macro_step', hue='data_augmentation', \n",
    "    data=pd.concat([df_train_augmented, df_train_non_augmented]), \n",
    "    ax=axs[1, 1]\n",
    ")\n",
    "axs[1, 1].set_ylabel('')\n",
    "axs[1, 1].legend(title='data augmentation')\n",
    "\n",
    "axs[0, 0].set_title('validation metrics')\n",
    "axs[0, 1].set_title('training metrics')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('/dss/dsshome1/04/di93zer/git/cellnet/figure-plots/figure3/training-curves.pdf')\n",
    "plt.savefig('/dss/dsshome1/04/di93zer/git/cellnet/figure-plots/figure3/training-curves.png', dpi=300)"
   ]
  },
  {
   "cell_type": "raw",
   "id": "ade307da-dd7f-4aed-9609-ce0d8127f44a",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c7eb3bab-3623-4a1d-b9e2-d05e906d2b3a",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Evaluate performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8ce0d628-1f83-4c1a-96a4-fb0b8811a7af",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "torch.set_float32_matmul_precision('high')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f5d41f5a-ac13-4d4e-a240-a21a1e289243",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/merlin/dtypes/mappings/tf.py:52: UserWarning: Tensorflow dtype mappings did not load successfully due to an error: No module named 'tensorflow'\n",
      "  warn(f\"Tensorflow dtype mappings did not load successfully due to an error: {exc.msg}\")\n"
     ]
    }
   ],
   "source": [
    "from os.path import join\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import lightning.pytorch as pl\n",
    "import dask.dataframe as dd\n",
    "\n",
    "from cellnet.estimators import EstimatorCellTypeClassifier\n",
    "from cellnet.models import TabnetClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7e848203-68d9-4033-aabe-9a4e114b54a3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "DATA_PATH = '/mnt/dssmcmlfs01/merlin_cxg_2023_05_15_sf-log1p'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "da1abe1d-b590-4ded-8383-810aa611c65e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import gc\n",
    "\n",
    "\n",
    "try:\n",
    "    res_df = pd.read_csv('augmentation_results_subset.csv')\n",
    "except FileNotFoundError:\n",
    "    res_df = pd.DataFrame(\n",
    "        {'test_loss': [], 'test_f1_macro': [], 'data_augmentation': [], 'ckpt': []}\n",
    "    )\n",
    "\n",
    "\n",
    "estim = EstimatorCellTypeClassifier(DATA_PATH)\n",
    "estim.init_datamodule(batch_size=4096)\n",
    "estim.trainer = pl.Trainer(logger=[], accelerator='gpu', devices=1)\n",
    "\n",
    "results = {'test_loss': [], 'test_f1_macro': [], 'data_augmentation': [], 'ckpt': []}\n",
    "for augment, ckpts in [(True, best_ckpts_augmented), (False, best_ckpts_non_augmented)]:\n",
    "    for ckpt in ckpts:\n",
    "        if ckpt in res_df.ckpt.tolist():\n",
    "            run = res_df.ckpt == ckpt\n",
    "            loss_ckpt = float(res_df.loc[run, 'test_f1_macro'])\n",
    "            f1_ckpt = float(res_df.loc[run, 'test_f1_macro'])\n",
    "            print(\n",
    "                f\"Reusing {ckpt.split('/')[-1]} checkpoint: f1-score={f1_ckpt:.4f} loss={loss_ckpt:.4f}\"\n",
    "            )\n",
    "            results['test_loss'].append(loss_ckpt)\n",
    "            results['test_f1_macro'].append(f1_ckpt)\n",
    "            results['data_augmentation'].append(augment)\n",
    "            results['ckpt'].append(ckpt)\n",
    "        else:\n",
    "            estim.model = TabnetClassifier.load_from_checkpoint(ckpt, **estim.get_fixed_model_params('tabnet'))\n",
    "            res = estim.test()[0]\n",
    "            results['test_loss'].append(res['test_loss'])\n",
    "            results['test_f1_macro'].append(res['test_f1_macro'])\n",
    "            results['data_augmentation'].append(augment)\n",
    "            results['ckpt'].append(ckpt)\n",
    "            gc.collect()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f837d58e-0545-4ce3-b7d7-c010cfa1d7f8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "res_df = pd.DataFrame(results)\n",
    "res_df.to_csv('augmentation_results_subset.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3fbfc438-f126-42ba-99ab-b60c23f4da19",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "a8923002-92ba-4e51-a9e3-7afbf2409785",
   "metadata": {},
   "source": [
    "#### Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d6e93d9b-42d9-4a06-8d68-cff7a2e66617",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from statistics import mean, stdev\n",
    "from scipy.stats import ttest_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2bef0704-0e6d-4dbe-82e9-5c1d8a53e599",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "loss_augment = res_df[res_df.ckpt.isin(best_ckpts_augmented)]['test_loss'].tolist()\n",
    "loss_non_augment = res_df[res_df.ckpt.isin(best_ckpts_non_augmented)]['test_loss'].tolist()\n",
    "f1_augment = res_df[res_df.ckpt.isin(best_ckpts_augmented)]['test_f1_macro'].tolist()\n",
    "f1_non_augment = res_df[res_df.ckpt.isin(best_ckpts_non_augmented)]['test_f1_macro'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "595c5254-18ec-4570-b44d-02eb7b6431a9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neg. log-likelihood</th>\n",
       "      <th>F1-score (macro avg.)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>w. augmentation</th>\n",
       "      <td>0.659 +/- 0.04</td>\n",
       "      <td>0.7841 +/- 0.003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>wo. augmentation</th>\n",
       "      <td>0.797 +/- 0.05</td>\n",
       "      <td>0.7755 +/- 0.002</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Neg. log-likelihood F1-score (macro avg.)\n",
       "w. augmentation       0.659 +/- 0.04      0.7841 +/- 0.003\n",
       "wo. augmentation      0.797 +/- 0.05      0.7755 +/- 0.002"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame({\n",
    "    'Neg. log-likelihood': [\n",
    "        f\"{mean(loss_augment):.3} +/- {stdev(loss_augment):.1}\", \n",
    "        f\"{mean(loss_non_augment):.3} +/- {stdev(loss_non_augment):.1}\"\n",
    "    ],\n",
    "    'F1-score (macro avg.)': [\n",
    "        f\"{mean(f1_augment):.4} +/- {stdev(f1_augment):.1}\",\n",
    "        f\"{mean(f1_non_augment):.4} +/- {stdev(f1_non_augment):.1}\"\n",
    "    ]\n",
    "}, index=['w. augmentation', 'wo. augmentation'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "378ddecb-06b7-494a-9e40-b5cb31600663",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from IPython.display import display\n",
    "pd.options.display.float_format = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b7809c6c-4383-41da-9b80-f0246676e0bb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Neg. log-likelihood</th>\n",
       "      <th>F1-score (macro avg.)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>percentage change</th>\n",
       "      <td>-20.9%</td>\n",
       "      <td>1.1%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>p value</th>\n",
       "      <td>0.00388</td>\n",
       "      <td>0.001615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>significant</th>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Neg. log-likelihood F1-score (macro avg.)\n",
       "percentage change              -20.9%                  1.1%\n",
       "p value                       0.00388              0.001615\n",
       "significant                      True                  True"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pct_change_loss = 1. - mean(loss_non_augment) / mean(loss_augment)\n",
    "pct_change_f1 = 1. - mean(f1_non_augment) / mean(f1_augment)\n",
    "\n",
    "\n",
    "pd.DataFrame({\n",
    "    'Neg. log-likelihood': [\n",
    "        f'{pct_change_loss * 100.:.3}%',\n",
    "        ttest_ind(loss_non_augment, loss_augment).pvalue,\n",
    "        ttest_ind(loss_non_augment, loss_augment).pvalue <= 0.05\n",
    "    ],\n",
    "    'F1-score (macro avg.)': [\n",
    "        f'{pct_change_f1 * 100.:.2}%',\n",
    "        ttest_ind(f1_non_augment, f1_augment).pvalue,\n",
    "        ttest_ind(f1_non_augment, f1_augment).pvalue <= 0.05\n",
    "    ],\n",
    "}, index=['percentage change', 'p value', 'significant'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "54121b23-fe6e-4c7d-a25a-39d4fb026611",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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